1. Field of the Invention
This invention generally relates to the field of exploring underground rock and hydrocarbon formations. In particular, the present invention is directed to a method and apparatus for using nanorobots to move through a subsurface formation to identify various geophysical characteristics.
2. Description of the Related Art
The overriding problem in exploring for hydrocarbons in the subsurface is the probing in, and characterizing of, an environment that cannot be seen. Similarly once a commercial hydrocarbon deposit has been discovered and is about to be developed and exploited much conjecture and many assumptions must be made by reservoir geologists and reservoir engineers in the modeling of a large volume of rock which cannot be seen.
Subsurface reservoir data is currently acquired from probes lowered into boreholes and from images (seismography). In the first instance, the data is handicapped by its insufficiency, by virtue of being sourced from a single 6-inch hole, thus giving too narrow of a view. The interpreted seismic volumes, on the other hand, gives too broad of a view due to their imaging quality and resolution inadequacies. Even combining the two, will not enable for the mapping of exact high permeability pathways.
The integration of available geological, geophysical, petrophysical engineering, and drilling data makes interesting inroads into the detection, mapping and predictive modeling of high permeability pathways. The final uncertainty of integrated models, however, can only be marginally better than the average uncertainty inherent in the various methods used. Mix and integrate as much as one may, the broad brush strokes on reservoir map deliverables, will remain just that: broad brush. A 0.5 mm scribble drawn on a 1:200,000 scale map to represent a fracture in the subsurface, is akin to depicting a fracture with an aperture of 200 m because of the width of the scribble relative to the scale of the map. The scribble will not reveal the precise path that the fluids are likely to take.
As oil fields mature, it can be expected that fluid injection for pressure support (secondary enhanced oil recovery) will increasingly tend to erratically invade, and irregularly sweep, the residual oil leg. At the close of the second millennium, petroleum concerns were seen scrambling to mobilize however possible in order to identify, detect and map pathways that may lead injected fluids prematurely updip along encroachment fingers. More often than not, the encroachment materializes faster than even the worst expectations, and commonly in quite unpredictable directions. Moreover, premature encroachment is commonly tortuous and will change direction in 3D volume, much like a rubber ball wildly bounced about in a cubic enclosure. This type of tortuousity renders high permeability pathway prediction almost impossible to satisfactorily pin down. In spite of an arsenal of cutting-edge technologies thrown at such problems, high permeability pathway prediction capability continues to suffer from high levels of uncertainty.
Post mortem and predictive mapping of erratically occurring high permeability pathways is a leading issue of concern to major petroleum companies. The solution to the problem is currently sought through the manipulation of data acquired directly from the borehole and indirectly, through map view representations of faults or fracture swarms or horizontal permeability (“kh”) from pressure buildups. Permeability pathways are interwell phenomena. Unfortunately, it is interwell control that is very difficult to characterize.
With current technology, it is impossible to work out the exact pathway that fluid fingering takes as it invades deep into an oil leg, much less where it will go next. Engineering data (e.g. water arrival data—i.e., water arrival detected in an oil producing well, flowmeter data, test kh build-up, pressure data, and productivity/infectivity data), although mostly acquired at the borehole, are typically correlated aerially. The resultant maps are a very indirect, unreliable and a crude way of trying to depict the reservoir geology of a reservoir. The resultant maps are interpretive, and reservoir engineers are the first to dissociate them from being accurate reflections of specific geologic features. Moreover, the map resolutions are too broad to even remotely represent most geological features that would commonly be associated with high permeability pathways.
Other interwell methods to map permeability pathways are, likewise, handicapped by resolution problems. Geophysical technologies rooted in interpreting 3D, 4D, shear wave, or multi-component volumes; even when utilizing ever-developing clarity and resolution enhancing software packages, still only render a generalized mapping of a miniscule sampling of some faults in the general area where they may or may not be located.
In carbonate rocks, fractures with apertures measured in millimeters, or geobodies only centimeters across, can provide the necessary plumbing to take injected fluid past matrixed oil. To further illustrate this, a 3 cm wide fracture with no displacement may, under pressure, move fluids at several Darcies. These dimensions cannot be seen by current interpretive geophysical devices. Subsequently, the fault lines drawn on reservoir structure maps cannot be considered more than broad arrows pointing out a general direction; and not a depiction of actual permeability pathways. Furthermore, geophysically-interpreted data must be augmented by a solid understanding of the regional stress-strain regimes in order to filter out fracture swarms which may not be contributing to premature fluid breakthroughs.
Dyes and radioactive chemicals (tracers) introduced with injected fluids can be locally helpful, but they will not reveal the actual pathway taken by the host fluid from the entry well to the detection well. Borehole detection methods are the most exact, but they are also afflicted with major shortcomings. The immediately obvious shortcoming is that, for mapping purposes, wellsite data must be extrapolated and transformed into interwell information. Extrapolation in itself is the problem.
Any sedimentologist will sympathize with the deposition heterogeneities with or without a structural overprint. The slightest shifts in water depth, measured in decimeters, can create worlds of difference in depositional fabric. Moreover, rock minerals, especially carbonates, are in continuous “life long” effective diagenesis from the instant of deposition. There is no carbonate porosity that has not been dictated by deposition and then unceasingly altered by diagenesis. One can already see the problem of interwell extrapolation from well control.
The geostatistical distribution of attributes, including fractures detected on borehole image logs, at the wellbore, is the best we've got; but it is only statistical, and natural geological landscapes are too variable and rugose to respond comfortably to the smooth, clean logic of mathematics. Much like fingerprints, there are no two features in carbonate rocks that are the same. Extrapolation in the complex world of carbonate geology has a long way to go.
Adding to the difficulties of borehole solutions is that the geological features contributing to abnormally high flow rates are, like some rare species, rarely captured in rock cores. Consequently reservoir geologists are, in most cases, disallowed the opportunity to properly study and characterize reservoir problems.